Gen AI Developer

Role: Gen AI Developer

Experience: 1–6 Years

Location: Remote/HYD/BLR/Chennai

Notice Period: maximum 30 days

Educational Criteria:

Looking B.Tech graduates only from NIT/IIT with degrees in the following disciplines:

• Computer Science & Engineering (CSE)
• Electronics & Communication Engineering (ECE)
• Mathematics and Computing
• Computer Science & Business System
• Artificial Intelligence and Machine learning
• Robotics and Automation Engineering
• Artificial Intelligence and Data science
• Information Technology (IT)Skills
• End-to-end delivery of Gen AI solutions inside a client engagement — from discovery to production
• Architecture decisions on document pipelines, agent systems, RAG infrastructure, copilots, and operational AI
• Hardening LLM features: evals, prompt versioning, cost & latency optimization, observability, guardrails
• Stakeholder management — translating client problems into technical scope, and technical realities back into business language

We are Looking Skills

• 2–5 years of software engineering experience with at least one product/major feature shipped to real users
• Strong Python plus one of TypeScript / Go / Java
• Comfortable working across the stack when required
• Proven production GenAI/LLM experience — not just POCs or demos
• Experience with LLM cost, latency, prompt versioning and evaluation (evals)
• Strong understanding of system design and distributed systems
• Hands-on experience with vector databases such as Pinecone, Weaviate or pgvector
• Cloud experience with AWS / Azure / GCP
• Comfortable working directly with PMs, stakeholders or clients
• At least one 0-to-1 project owned end-to-end
• Experience using Claude Code, Cursor, GitHub Copilot, Windsurf or similar GenAI coding tools, with the ability to critically review AI-generated code

Preferred

• Built or contributed to internal tooling/platforms used by other engineers
• Vertical domain depth — BFSI, healthcare, telecom, retail, or insurance
• Eval frameworks experience (Braintrust, LangSmith, internal eval pipelines)
• Experience with MCP servers, agent frameworks, multi-agent orchestration
• Have broken production at least once on an architectural choice — and can articulate the lesson